AB0008 ACESO APPLICATION: AN INTEGRATED GENOTYPE ANALYSIS WEB SERVER FOR CLINICAL GENOMICS IN CROHN’S DISEASE AND IBD-RELATED ARTHRITIS
Authors: L. Papageorgiou, M. Zervou, I. Katsimpoula, D. Vlachakis, G. Bertsias, G. Goulielmos, E. Eliopoulos
Journal: Annals of the Rheumatic Diseases (2022)

Background Genome Wide Association Studies (GWAS) observe the set of different variants throughout the genome of different individuals and study whether a particular trait is due to one variant. Many autoimmune diseases have been identified to have a linkage with specific loci and metabolic pathways, but the exact cause of disorders is still remaining unknown [1]. Aceso Application is an integrated bioinformatics web-tool designed for researchers and medical experts towards to estimating the clinical genomic profile of a candidate patient with Crohn’s Disease (CD)[2-4]. Objectives To identify the most reliable gene variants, single nucleotide polymorphisms (SNPs) and epigenetic related SNPs that causing CD using the genomic data provided for the patient and aid the medical expert in CD diagnosis. Methods In the present study, we have analyzed more than 149.000 CD related publications using data mining and semantic techniques towards extracting the Crohn’s Disease-related genes, non-coding regions and generally candidate SNPs. The extracted knowledge has been filtered, evaluated, annotated, classified, and stored in the Aceso Application Database (AAD). This was followed by the design and development of the Aceso application, in which the generated datasets and results were included. The application has been tested and presented here with whole-exome sequencing data from several related patients with CD. Results CD-related SNPs and variants identified in genome-wide association studies (GWAS), whole-genome (WGS), whole-exome (WES), or targeted sequencing information are classified, annotated, and analyzed in an integrated patient profile with clinical significance information. Probable genes associated with the patient’s genomic profile are visualized with chromosome ideograms, statistic bars, and regulatory networks through data mining studies with relative publications. An evaluation study was performed on 2 patients from a three-generation family with CD [5]. Conclusion The Aceso application was designed to assist early stage diagnosis by using the patients’s genomic data. It provides the patient’s genomic profile which is generated based on the list of the most predictable candidate gene variants related to CD and has implications also for IBD-related arthritis. This novel and accessible webserver tool of CD to assist medical experts in the clinical genomics and precision medicine procedure is available at http://geneticslab.aua.gr/aceso . References [1]Ramos et al, J Hum Genet 2015; 60 :657 [2]Papageorgiou et al, Int J Mol Med 2022; 49 :8 [3]Papageorgiou et al, Int J Mol Med 2021; 47 :115 [4]Van Limbergen and Satsangi, Annu Rev Genomics Hum Genet 2009; 10 :89 [5]Albertsen et al, Mol Med Rep 2019; 19 :1716 Figure 1. The Aceso app web-server Database. Left are shown the three identified SNPs classes of the genomic “grammar“ of CD. Disclosure of Interests None declared